package com.yupi.yuaiagent.app;

import com.yupi.yuaiagent.advisor.MyLoggerAdvisor;
import com.yupi.yuaiagent.chatMemory.FileBasedChatMemory;
import jakarta.annotation.Resource;
import lombok.extern.slf4j.Slf4j;
import org.springframework.ai.chat.client.ChatClient;
import org.springframework.ai.chat.client.advisor.MessageChatMemoryAdvisor;
import org.springframework.ai.chat.client.advisor.QuestionAnswerAdvisor;
import org.springframework.ai.chat.client.advisor.api.Advisor;
import org.springframework.ai.chat.memory.ChatMemory;
import org.springframework.ai.chat.memory.InMemoryChatMemory;
import org.springframework.ai.chat.model.ChatModel;
import org.springframework.ai.chat.model.ChatResponse;
import org.springframework.ai.tool.ToolCallback;
import org.springframework.ai.tool.ToolCallbackProvider;
import org.springframework.ai.vectorstore.VectorStore;
import org.springframework.stereotype.Component;

import java.util.List;

import static org.springframework.ai.chat.client.advisor.AbstractChatMemoryAdvisor.CHAT_MEMORY_CONVERSATION_ID_KEY;
import static org.springframework.ai.chat.client.advisor.AbstractChatMemoryAdvisor.CHAT_MEMORY_RETRIEVE_SIZE_KEY;

@Slf4j
@Component
public class LoveApp {

    private ChatClient chatClient;

    @Resource
    private VectorStore loveAppVectorStore;


    private static final String SYSTEM_PROMPT = "扮演深耕恋爱心理领域的专家"/*"扮演深耕恋爱心理领域的专家。开场向用户表明身份，告知用户可倾诉恋爱难题。" +
                "围绕单身、恋爱、已婚三种状态提问：单身状态询问社交圈拓展及追求心仪对象的困扰；" +
                "恋爱状态询问沟通、习惯差异引发的矛盾；已婚状态询问家庭责任与亲属关系处理的问题。" +
                "引导用户详述事情经过、对方反应及自身想法，以便给出专属解决方案。"*/;


                //dashscopeChatModel
    //ollamaChatModel
    public LoveApp(ChatModel dashscopeChatModel) {
        ChatMemory chatMemory = new InMemoryChatMemory();
        String fileDir = System.getProperty("user.dir") + "/tmp/chat-memory";
        ChatMemory fileChatMemory = new FileBasedChatMemory(fileDir);

        chatClient = ChatClient.builder(dashscopeChatModel)
                .defaultSystem(SYSTEM_PROMPT)
                .defaultAdvisors(new MessageChatMemoryAdvisor(fileChatMemory),
                        new MyLoggerAdvisor()
                )
                .build();
    }

    public String doChat(String message, String chatId) {
        ChatResponse response = chatClient.prompt()
                .user(message)
                .advisors(spec -> spec.param(CHAT_MEMORY_CONVERSATION_ID_KEY, chatId)
                        .param(CHAT_MEMORY_RETRIEVE_SIZE_KEY, 1))
                .call()
                .chatResponse();

        String content = response.getResult().getOutput().getText();
        log.info("content:{}", content);
        return content;
    }

    record LoveReport(String title, List<String> suggestions){};

    public LoveReport doChatWithReport(String message, String chatId) {
        LoveReport loveReport = chatClient
                .prompt()
                .system(SYSTEM_PROMPT + "每次对话后都要生成恋爱结果，标题为{用户名}的恋爱报告，内容为建议列表")
                .user(message)
                .advisors(spec -> spec.param(CHAT_MEMORY_CONVERSATION_ID_KEY, chatId)
                        .param(CHAT_MEMORY_RETRIEVE_SIZE_KEY, 10))
                .call()
                .entity(LoveReport.class);
        log.info("loveReport: {}", loveReport);
        return loveReport;
    }

    public String doChatWithRag(String message, String chatId) {
        ChatResponse chatResponse = chatClient
                .prompt()
                .user(message)
                .advisors(spec -> spec.param(CHAT_MEMORY_CONVERSATION_ID_KEY, chatId)
                        .param(CHAT_MEMORY_RETRIEVE_SIZE_KEY, 10))
                // 开启日志， 便于观察结果
                .advisors(new MyLoggerAdvisor())
                .advisors(new QuestionAnswerAdvisor(loveAppVectorStore))
                .call()
                .chatResponse();
        String content = chatResponse.getResult().getOutput().getText();
        log.info("content:{}", content);
        return content;
    }

    @Resource
    private Advisor loveAppRagCloudAdvisor;

    public String doChatWithRagCloud(String message, String chatId) {
        ChatResponse chatResponse = chatClient
                .prompt()
                .user(message)
                .advisors(spec -> spec.param(CHAT_MEMORY_CONVERSATION_ID_KEY, chatId)
                        .param(CHAT_MEMORY_RETRIEVE_SIZE_KEY, 10))
                // 开启日志， 便于观察结果
                .advisors(loveAppRagCloudAdvisor)
                .call()
                .chatResponse();
        String content = chatResponse.getResult().getOutput().getText();
        log.info("content:{}", content);
        return content;
    }

    @Resource
    private ToolCallback[] allTools;

    public String doChatWithTools(String message, String chatId) {
        ChatResponse response = chatClient
                .prompt()
                .user(message)
                .advisors(spec -> spec.param(CHAT_MEMORY_CONVERSATION_ID_KEY, chatId)
                        .param(CHAT_MEMORY_RETRIEVE_SIZE_KEY, 10))
                .tools(allTools)
                .call()
                .chatResponse();
        String content = response.getResult().getOutput().getText();
        log.info("content: {}", content);
        return content;
    }

    @Resource
    private ToolCallbackProvider toolCallbackProvider;

    public String doChatWithMcp(String message, String chatId) {
        ChatResponse response = chatClient
                .prompt()
                .user(message)
                .advisors(spec -> spec.param(CHAT_MEMORY_CONVERSATION_ID_KEY, chatId)
                        .param(CHAT_MEMORY_RETRIEVE_SIZE_KEY, 10))
                .tools(toolCallbackProvider)
                .call()
                .chatResponse();
        String content = response.getResult().getOutput().getText();
        log.info("content: {}", content);
        return content;
    }

}
